Biography
I am the Director of the ADAPT Research Center (www.adaptcentre.ie) and the Professor of Computer Science (2016) at the School of Computer Science and Statistics at Trinity College Dublin. My journey in academia began with a BSc. in Computer Applications from Dublin City University in 1997. In 2003, I completed my PhD in Artificial Intelligence, also at Dublin City University, focusing on the intersection of language and vision within the context of situated dialogue. This research studied how humans interact with robots or virtual environments through language, paving the way for advancements in human-computer dialogue systems, and artificial intelligence. Following my doctoral studies, I worked as a post-doctoral researcher at Media Lab Europe and the German Centre for Artificial Intelligence (DFKI). In 2005, I joined the faculty of the School of Computer Science at the Dublin Institute of Technology, later transitioning to Technological University Dublin. In 2017 my research and teaching work was recognized with my appointment as Professor by the Dublin Institute of Technology. I joined the Hamilton Research Institute at Maynooth University as a Professor of Computer Science in 2023. In 2024, I was appointed to the role of Professor of Computer Science at Trinity College Dublin's School of Computer Science and Statistics. Concurrently, I lead the ADAPT Research Center, driving innovation and collaboration in the dynamic field of computer science.
Publications and Further Research Outputs
Peer-Reviewed Publications
Abbas A.N, Chasparis G.C, Kelleher J.D, Specialized Deep Residual Policy Reinforcement Learning Framework for Safe and Adaptive Continuous Control, IET Control Theory and Applications, 20, (1), 2026
Vasudevan Nedumpozhimana and John Kelleher, Know Yourself and Know Your Neighbour : A Syntactically Informed Self-Supervised Compositional Sentence Representation Learning Framework using a Recursive Hypernetwork, Transactions on Machine Learning Research, 2025
Mehak S, Jain A, Kelleher J.D, Guilfoyle M, Long P, Leva M.C, A multimodal dataset for human robot collaborative systems: Experimental data, Data in Brief, 63, 2025
Ale, Seun and Hunter, Elizabeth and Kelleher, John D., Correction to: Agent based modelling of blood borne viruses: a scoping review (BMC Infectious Diseases, (2024), 24, 1, (1411), 10.1186/s12879-024-10271-w), BMC Infectious Diseases, 25, (1), 2025
Jeffrey Sardina, John D. Kelleher, Declan O'Sullivan, A Survey on Graph Structure and Knowledge Graph Embeddings, IEEE 19th International Conference on Semantic Computing, Laguna Hills,California, USA, 3-5 Feb 2025, IEEE Computer Society Press, 2025, pp1 - 10
Vasudevan Nedumpozhimana, John Kelleher, Topic aware probing: From sentence length prediction to idiom identification how reliant are neural language models on topic?, Natural Language Processing, 31, 2025, p936 - 964
Jeffrey Sardina, John Kelleher, Declan O'Sullivan, Structural Alignment of Knowledge Graphs and Link Prediction: A Survey of the Literature, International Journal of Semantic Computing, 2025, p1 - 25
Caglayan, Bora and Wang, Mingxue and Kelleher, John D. and Fei, Shen and Tong, Gui and Ding, Jiandong and Zhang, Puchao, BIS: NL2SQL Service Evaluation Benchmark for Business Intelligence Scenarios, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 15405 LNCS, 2025, p357 â" 372
Jawla, Devesh and Kelleher, John, Layer wise Scaled Gaussian Priors for Markov Chain Monte Carlo Sampled deep Bayesian neural networks, Frontiers in Artificial Intelligence, 8, 2025
Cisek K.K., Nguyen T.N.Q., Garcia-Rudolph A., Sauri J., Becerra Martinez H., Hines A., Kelleher J.D., Predictors of social risk for post-ischemic stroke reintegration, Scientific Reports, 14, (1), 2024
Abbas, A.N. and Amazu, C.W. and Mietkiewicz, J. and Briwa, H. and Perez, A.A. and Baldissone, G. and Demichela, M. and Chasparis, G.C. and Kelleher, J.D. and Leva, M.C., Analyzing Operator States and the Impact of AI-Enhanced Decision Support in Control Rooms: A Human-in-the-Loop Specialized Reinforcement Learning Framework for Intervention Strategies, International Journal of Human-Computer Interaction, 2024
KlubiÄ ka, F. and Kelleher, J.D., ReproHum #1018-09: Reproducing Human Evaluations of Redundancy Errors in Data-To-Text Systems, 2024, pp163-198
Jain, A. and Long, P. and Villani, V. and Kelleher, J.D. and Chiara Leva, M., CoBT: Collaborative Programming of Behaviour Trees from One Demonstration for Robot Manipulation, 2024, pp12993-12999
Sardina, Jeffrey and Kelleher, John D. and O'Sullivan, Declan, TWIG: Towards pre-hoc Hyperparameter Optimisation and Cross-Graph Generalisation via Simulated KGE Models, 2024 IEEE 18th International Conference on Semantic Computing (ICSC), 2024 IEEE 18th International Conference on Semantic Computing (ICSC), 2024, pp122-129
English, Patrick Cormac and Kelleher, John D. and Carson-Berndsen, Julie, Searching for Structure: Appraising the Organisation of Speech Features in wav2vec 2.0 Embeddings, 2024, pp4613 â" 4617
English, P.C. and Shams, E.A. and Kelleher, J.D. and Carson-Berndsen, J., FOLLOWING THE EMBEDDING: IDENTIFYING TRANSITION PHENOMENA IN WAV2VEC 2.0 REPRESENTATIONS OF SPEECH AUDIO, 2024, pp6685-6689
Hunter, E. and Kelleher, J.D., Estimating Population Burden of Stroke with an Agent-Based Model, Springer Proceedings in Complexity, 2024, p9-20
Rubab, Maira and Kelleher, John D. , Assessing the relative importance of vitamin D deficiency in cardiovascular health, Frontiers in Cardiovascular Medicine, 11, 2024
Abbas, Ammar N. and Mehak, Shakra and Chasparis, Georgios C. and Kelleher, John D. and Guilfoyle, Michael and Leva, Maria Chiara and Ramasubramanian, Aswin K., Safety-Driven Deep Reinforcement Learning Framework for Cobots: A Sim2Real Approach, 2024, pp2917 â" 2923
Mehak, Shakra and Ramos, Inês F. and Sagar, Keerthi and Ramasubramanian, Aswin and Kelleher, John D. and Guilfoyle, Michael and Gianini, Gabriele and Damiani, Ernesto and Leva, Maria Chiara, A roadmap for improving data quality through standards for collaborative intelligence in human-robot applications, Frontiers in Robotics and AI, 11, 2024
Patrick Cormac English, Erfan A. Shams, John D. Kelleher, Julie Carson-Berndsen, Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio, ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
Ale, Seun and Hunter, Elizabeth and Kelleher, John D., Agent based modelling of blood borne viruses: a scoping review, BMC Infectious Diseases, 24, (1), 2024
Abbas, A.N. and Chasparis, G.C. and Kelleher, J.D., Hierarchical framework for interpretable and specialized deep reinforcement learning-based predictive maintenance, Data and Knowledge Engineering, 149, (102240), 2024
English, Patrick Cormac and Shams, Erfan A. and Kelleher, John D. and Carson-Berndsen, Julie, Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio, IEEE Xplore, ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, Republic of, 14-19 April 2024, IEEE, 2024, pp6685 - 6689
Helard Becerra Martinez, Katryna Cisek, Alejandro García-Rudolph, John D. Kelleher, Andrew Hines, Transparently Predicting Therapy Compliance of Young Adults Following Ischemic Stroke, Communications in Computer and Information Science, 2024
Mehak S., Kelleher J.D., Guilfoyle M., Leva M.C., Action Recognition for Human"Robot Teaming: Exploring Mutual Performance Monitoring Possibilities, Machines, 12, (1), 2024
Sardina, Jeffrey and Kelleher, John D. and Oâ Sullivan, Declan, Extending TWIG: Zero-Shot Predictive Hyperparameter Selection for KGEs based on Graph Structure, 3910, 2024, pp76 â" 88
Jeffrey Sardina, John D. Kelleher, Declan O"Sullivan, TWIG: Towards pre-hoc Hyperparameter Optimisation and Cross-Graph Generalisation via Simulated KGE Models, 2024 IEEE 18th International Conference on Semantic Computing (ICSC), 2024
Eduardo Cueto-Mendoza and John D. Kelleher, A framework for measuring the training efficiency of a neural architecture, Artificial Intelligence Review, 57, (349), 2024, p1 - 33
Martinez H.B., Cisek K., Garcia-Rudolph A., Kelleher J.D., Hines A., Transparently Predicting Therapy Compliance of Young Adults Following Ischemic Stroke, Communications in Computer and Information Science, 2156 CCIS, 2024, p24 - 41, p24-41
Jennifer Scott, Arthur White, Cathal Walsh, Louis Aslett, Matthew A Rutherford, James Ng, Conor Judge, Kuruvilla Sebastian, Sorcha O'Brien, John Kelleher, Julie Power, Niall Conlon, Sarah M Moran, Raashid Ahmed Luqmani, Peter A Merkel, Vladimir Tesar, Zdenka Hruskova Mark A Little, Computable phenotype for real-world, data-driven retrospective identification of relapse in ANCA-associated vasculitis, RMD Open, 10, (2), 2024, p1-11
Nguyen, Thi Nguyet Que and GarcÃa-Rudolph, Alejandro and SaurÃ, Joan and Kelleher, John D. , Multi-task learning for predicting quality-of-life and independence in activities of daily living after stroke: a proof-of-concept study, Frontiers in Neurology, 15, 2024
GarcÃa-Rudolph, A. and Sanchez-Pinsach, D. and Frey, D. and Opisso, E. and Cisek, K. and Kelleher, J.D., Know an Emotion by the Company It Keeps: Word Embeddings from Reddit/Coronavirus, Applied Sciences (Switzerland), 13, (11), 2023
Lindh, A. and Ross, R. and Kelleher, J.D., Show, Prefer and Tell: Incorporating User Preferences into Image Captioning, 2023, pp1139-1142
KlubiÄ ka, F. and Kelleher, J.D., HumEvalâ 23 Reproduction Report for Paper 0040: Human Evaluation of Automatically Detected Over- and Undertranslations, 2023, pp153-189
Moslem, Y. and Romani, G. and Molaei, M. and Haque, R. and Kelleher, J.D. and Way, A., Domain Terminology Integration into Machine Translation: Leveraging Large Language Models, 2023, pp900-909
KlubiÄ ka, F. and Kelleher, J.D., Probing Taxonomic and Thematic Embeddings for Taxonomic Information, 2023, pp1-13
Nedumpozhimana, V. and Rautmare, S. and Gower, M. and Popovic, M. and Jain, N. and Buffini, P. and Kelleher, J., Medical Concept Mention Identification in Social Media Posts using a Small Number of Sample References, 2023, pp777-784
Hunter, E. and Kelleher, J.D., Determining the Proportionality of Ischemic Stroke Risk Factors to Age, Journal of Cardiovascular Development and Disease, 10, (2), 2023
Nayak, P. and Haque, R. and Kelleher, J.D. and Way, A., Instance-Based Domain Adaptation for Improving Terminology Translation, 1, 2023, pp222-234
Jafaritazehjani, S. and Lecorvé, G. and Lolive, D. and Kelleher, J.D., Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14263 LNCS, 2023, p492-504
Cisek, K. and Kelleher, J.D., Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content Analysis, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 2023, p3341-3352
PopoviÄ , M. and Nedumpozhimana, V. and Gower, M. and Rautmare, S. and Jain, N. and Kelleher, J., Using MT for multilingual covid-19 case load prediction from social media texts, 2023, pp461-470
Belz, A. and Thomson, C. and Reiter, E. and Abercrombie, G. and Alonso-Moral, J.M. and Arvan, M. and Braggaar, A. and Cieliebak, M. and Clark, E. and van Deemter, K. and Dinkar, T. and DuÅ¡ek, O. and Eger, S. and Fang, Q. and Gao, M. and Gatt, A. and Gkatzia, D. and González-Corbelle, J. and Hovy, D. and HÃŒrlimann, M. and Ito, T. and Kelleher, J.D. and KlubiÄ ka, F. and Krahmer, E. and Lai, H. and van der Lee, C. and Li, Y. and Mahamood, S. and Mieskes, M. and van Miltenburg, E. and Mosteiro, P. and Nissim, M. and Parde, N. and Plátek, O. and Rieser, V. and Ruan, J. and Tetreault, J. and Toral, A. and Wan, X. and Wanner, L. and Watson, L. and Yang, D., Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP, 2023, pp1-10
KlubiÄ ka, F. and Nedumpozhimana, V. and Kelleher, J.D., Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space, 2023, pp45-57
Hunter, E. and Saha, S. and Kumawat, J. and Carroll, C. and Kelleher, J.D. and Buckley, C. and McAloon, C. and Kearney, P. and Gilbert, M. and Martin, G., Assessing the impact of contact tracing with an agent-based model for simulating the spread of COVID-19: The Irish experience, Healthcare Analytics, 4, (100229), 2023
Garcia-Rudolph, A. and Sauri, J. and Cisek, K. and Kelleher, J.D. and Madai, V.I. and Frey, D. and Opisso, E. and Tormos, J.M. and Bernabeu, M., Long-term trajectories of community integration: identification, characterization, and prediction using inpatient rehabilitation variables, Topics in Stroke Rehabilitation, 30, (7), 2023, p714-726
Sardina, J. and Sardina, C. and Kelleher, J.D. and Oâ Sullivan, D., Analysis of Attention Mechanisms in Box-Embedding Systems, Communications in Computer and Information Science, 1662 CCIS, 2023, p68-80
Mehak, S. and Leva, M.C. and Kelleher, J.D. and Guilfoyle, M., Action Classification in Human Robot Interaction Cells in Manufacturing: Moving Towards Mutual Performance Monitoring Capacity, 2023, pp214-220
English, P.C. and Kelleher, J.D. and Carson-Berndsen, J., Discovering Phonetic Feature Event Patterns in Transformer Embeddings, 2023-August, 2023, pp4733-4737
Moslem, Y. and Haque, R. and Kelleher, J.D. and Way, A., Adaptive Machine Translation with Large Language Models, 2023, pp227-237
Hunter, E. and Kelleher, J.D., A review of risk concepts and models for predicting the risk of primary stroke, Frontiers in Neuroinformatics, 16, (883762), 2022
Nayak, P. and Haque, R. and Kelleher, J.D. and Way, A., Investigating Contextual Influence in Document-Level Translation, Information (Switzerland), 13, (5), 2022
John D. Kelleher, Understanding the assumptions of an SEIR compartmental model using agentization and a complexity hierarchy, Journal of Computational Mathematics and Data Science, 4, 2022, p100056
Martinez, H.B. and Cisek, K. and GarcÃa-Rudolph, A. and Kelleher, J.D. and Hines, A., Understanding and Predicting Cognitive Improvement of Young Adults in Ischemic Stroke Rehabilitation Therapy, Frontiers in Neurology, 13, (886477), 2022
Nicholson, M. and Agrahari, R. and Conran, C. and Assem, H. and Kelleher, J.D., The interaction of normalisation and clustering in sub-domain definition for multi-source transfer learning based time series anomaly detection, Knowledge-Based Systems, 257, (109894), 2022
English, P.C. and Kelleher, J.D. and Carson-Berndsen, J., Domain-Informed Probing of wav2vec 2.0 Embeddings for Phonetic Features, 2022, pp83-91
Hunter, E. and Kelleher, J.D., Age Specific Models to Capture the Change in Risk Factor Contribution by Age to Short Term Primary Ischemic Stroke Risk, Frontiers in Neurology, 13, (803749), 2022
Jain, Aayush and Mehak, Shakra and Long, Philip and Kelleher, John D. and Guilfoyle, Michael and Leva, Maria Chiara, Evaluating Safety and Productivity Relationship in Human-Robot Collaboration, 2022, pp3218 â" 3225
GarcÃa-Rudolph, A. and SaurÃ, J. and Cegarra, B. and Madai, V.I. and Frey, D. and Kelleher, J.D. and Cisek, K. and Opisso, E. and Tormos, J.M. and Bernabeu, M., Long-term trajectories of motor functional independence after ischemic stroke in young adults: Identification and characterization using inpatient baseline assessments, NeuroRehabilitation, 50, (4), 2022, p453-465
Elizabeth Hunter, Bryony L. McGarry, John D. Kelleher, Simulating Delay in Seeking Treatment for Stroke Due to COVID-19 Concerns with a Hybrid Agent-Based and Equation-Based Model, 2022, p379--391
Abbas, Ammar N. and Chasparis, Georgios C. and Kelleher, John D., Deep Residual Policy Reinforcement Learning as a Corrective Term in Process Control for Alarm Reduction: A Preliminary Report, 2022, pp3260 â" 3266
Abbas, A.N. and Chasparis, G.C. and Kelleher, J.D., Interpretable Input-Output Hidden Markov Model-Based Deep Reinforcement Learning for the Predictive Maintenance of Turbofan Engines, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13428 LNCS, 2022, p133-148
Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos van Geffen, Michiel van Weele, Antonia Buettner, Tamara Wanigasekera, Cathal Walsh, Louis Aslett, John D Kelleher, Julie Power, James Ng, Declan O'Sullivan, Lucy Hederman, Neil Basu, Mark A Little, Lina Zgaga, The association between ambient UVB dose and ANCA-associated vasculitis relapse and onset, Arthritis Research & Therapy, 24, (1), 2022, p1 - 14
Tilda Herrgårdh, Elizabeth Hunter, Kajsa Tunedal, Håkan Örman, Julia Amann, Francisco Abad Navarro, Catalina Martinez-Costa, John D. Kelleher, Gunnar Cedersund, Digital twins and hybrid modelling for simulation of physiological variables and stroke risk, 2022
Nedumpozhimana, V. and KlubiÄ ka, F. and Kelleher, J.D., Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification, Frontiers in Artificial Intelligence, 5, (813967), 2022
Agrahari, R. and Nicholson, M. and Conran, C. and Assem, H. and Kelleher, J.D., Assessing Feature Representations for Instance-Based Cross-Domain Anomaly Detection in Cloud Services Univariate Time Series Data, IoT, 3, (1), 2022, p123-144
Hunter, E. and McGarry, B.L. and Kelleher, J.D., Simulating Delay in Seeking Treatment for Stroke Due to COVID-19 Concerns with a Hybrid Agent-Based and Equation-Based Model, 2022, pp379-391
Herrgårdh, T. and Madai, V.I. and Kelleher, J.D. and Magnusson, R. and Gustafsson, M. and Milani, L. and Gennemark, P. and Cedersund, G., Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios, NeuroImage: Clinical, 31, (102694), 2021
GarcÃa-Rudolph, A. and Kelleher, J.D. and Cegarra, B. and Ruiz, J.S. and Nedumpozhimana, V. and Opisso, E. and Tormos, J.M. and Bernabeu, M., The impact of body mass index on functional rehabilitation outcomes of working-age inpatients with stroke, European Journal of Physical and Rehabilitation Medicine, 57, (2), 2021, p216-226
Somayeh Jafaritazehjani and Gwé, Style as Sentiment Versus Style as Formality: The Same or Different?, Lecture Notes in Computer Science, 2021, p487--499
Hunter, E. and Kelleher, J.D., Using a hybrid agent-based and equation based model to test school closure policies during a measles outbreak, BMC Public Health, 21, (1), 2021
Zihni, Esra and Kelleher , John D. and McGarry, Bryony, An Analysis of the Interpretability of Neural Networks trained on Magnetic Resonance Imaging for Stroke Outcome Prediction , Proceedings of the International Society for Magnetic Resonance in Medicine, 2021
Peru Bhardwaj, John Kelleher, Luca Costabello, Declan O'Sullivan, Poisoning Knowledge Graph Embeddings via Relation Inference Patterns, Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Virtual, August 2021, 2021, pp16-30
Nedumpozhimana, V. and Kelleher, J.D., Finding BERTâ s Idiomatic Key, 2021, pp57-62
, Moving Toward Explainable Decisions of Artificial Intelligence Models for the Prediction of Functional Outcomes of Ischemic Stroke Patients, Digital Health, 2021
Jafaritazehjani, S. and Lecorvé, G. and Lolive, D. and Kelleher, J.D., Style as Sentiment Versus Style as Formality: The Same or Different?, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12895 LNCS, 2021, p487-499
Katryna Cisek and Thi Nguyet Que Nguyen and Alejandro Garcia-Rudolph and Joan Saur{\'{\i, Understanding Social Risk Variation Across Reintegration of Post-Ischemic Stroke Patients, Cerebral Ischemia, 2021, p201--220
Katryna Cisek and Thi Nguyet Que Nguyen and Alejandro Garcia-Rudolph and Joan Saur{\'{\i, Understanding Social Risk Variation Across Reintegration of Post-Ischemic Stroke Patients, Cerebral Ischemia, 2021, p201--220
Zihni, Esra and Kelleher , John D. and McGarry, Bryony, An Analysis of the Interpretability of Neural Networks trained on Magnetic Resonance Imaging for Stroke Outcome Prediction , Proceedings of the International Society for Magnetic Resonance in Medicine, 2021
Peru Bhardwaj, John Kelleher, Luca Costabello, Declan O'Sullivan, Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods, 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online and Punta Cana, Dominican Republic, November 2022, edited by Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih , Association for Computational Linguistics, 2021, pp8225-8239
Garcia-Rudolph, A. and Opisso, E. and Tormos, J.M. and Madai, V.I. and Frey, D. and Becerra, H. and Kelleher, J.D. and Guitart, M.B. and López, J., Toward personalized web-based cognitive rehabilitation for patients with ischemic stroke: Elo rating approach, JMIR Medical Informatics, 9, (11), 2021
Alejandro Garcia-Rudolph, Eloy Opisso, Jose M Tormos, Vince Istvan Madai, Dietmar Frey, Helard Becerra, John D Kelleher, Montserrat Bernabeu Guitart, Jaume López, Toward Personalized Web-Based Cognitive Rehabilitation for Patients With Ischemic Stroke: Elo Rating Approach (Preprint), 2021
Hunter, E. and Kelleher, J.D., Adapting an agent-based model of infectious disease spread in an irish county to covid-19, Systems, 9, (2), 2021
Kacmajor, M. and Kelleher, J.D., Capturing and measuring thematic relatedness, Language Resources and Evaluation, 54, (3), 2020, p645-682
Elizabeth Hunter, Brian Mac Namee, John D. Kelleher, A Model for the Spread of Infectious Diseases in a Region, International Journal of Environmental Research and Public Health, 17, (9), 2020, p3119
Kerr, A. and Barry, M. and Kelleher, J.D., Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance, Big Data and Society, 7, (1), 2020
Fernandez-Lopez, Adriana and Karaali, Ali and Harte, Naomi and Sukno, Federico M, ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp6294--6298
Mahalunkar, A. and Kelleher, J.D., Mutual Information Decay Curves and Hyper-parameter Grid Search Design for Recurrent Neural Architectures, Communications in Computer and Information Science, 1333, 2020, p616-624
Hunter E, Kelleher J, Using a Hybrid Agent-Based and Equation Based Model to Test School Closure Policies, 2020
Simon Dobnik, John D. Kelleher, Christine Howes, Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue, 2020, p251--267
Abhijit Mahalunkar, John D. Kelleher, Mutual Information Decay Curves and Hyper-parameter Grid Search Design for Recurrent Neural Architectures, 2020, p616--624
Dobnik, S. and Kelleher, J.D. and Howes, C., Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12162 LNAI, 2020, p251-267
Trinh, A.D. and Ross, R.J. and Kelleher, J.D., F-Measure Optimisation and Label Regularisation for Energy-Based Neural Dialogue State Tracking Models, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12397 LNCS, 2020, p798-810
Anh Duong Trinh, Robert J. Ross, John D. Kelleher, F-Measure Optimisation and Label Regularisation for Energy-Based Neural Dialogue State Tracking Models, 2020, p798--810
Livne, M. and Rieger, J. and Aydin, O.U. and Taha, A.A. and Akay, E.M. and Kossen, T. and Sobesky, J. and Kelleher, J.D. and Hildebrand, K. and Frey, D. and Madai, V.I., A U-net deep learning framework for high performance vessel segmentation in patients with cerebrovascular disease, Frontiers in Neuroscience, 13, (FEB), 2019
John D. Kelleher, Deep Learning, 1st Edition, MIT Press, The MIT Press, 2019, 1 - 296pp
Hossari, M. and Dev, S. and Kelleher, J.D., TEST: A terminology extraction system for technology related terms, 2019, pp78-81
Beauguitte, P. and Duggan, B. and Kelleher, J.D., Key inference from Irish traditional music scores and recordings, 2019, pp85-91
Hunter, E. and Namee, B.M. and Kelleher, J., Correction: An open-data-driven agent-based model to simulate infectious disease outbreaks (PLoS ONE (2018) 13:12 (e0208775) DOI: 10.1371/journal.pone.0208775), PLoS ONE, 14, (1), 2019
KlubiÄ ka, F. and Salton, G.D. and Kelleher, J.D., Is it worth it? Budget-related evaluation metrics for model selection, 2019, pp2014-2021
Kulkarni, V. and Mahalunkar, A. and Garbinato, B. and Kelleher, J.D., Examining the limits of predictability of human mobility, Entropy, 21, (4), 2019
Bacher, I. and Mac Namee, B. and Kelleher, J.D., Scoped: Evaluating A Composite Visualisation of the Scope Chain Hierarchy Within Source Code, (8530138), 2018, pp117-121
Wang, F., Ross, R.J., Kelleher, J.D., Exploring Online Novelty Detection Using First Story Detection Models, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11314 LNCS, 2018, p107-116
Hunter, E. and MacNamee, B. and Kelleher, J., A comparison of agent-based models and equation based models for infectious disease epidemiology, 2259, 2018, pp33-44
, Exploring the Functional and Geometric Bias of Spatial Relations Using Neural Language Models, Proceedings of the First International Workshop on Spatial Language Understanding, 2018
Ter-Sarkisov, A. and Ross, R. and Kelleher, J., Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis, 2018-January, 2018, pp277-284
, Data Science, MIT Press, 2018
Annika Lindh, Robert J. Ross, Abhijit Mahalunkar, Giancarlo Salton, John D. Kelleher, Generating Diverse and Meaningful Captions, 2018, p176--187
, Mind the Gap: Situated Spatial Language a Case-Study in Connecting Perception and Language, Proceedings of the Workshop on Dialogue and Perception, 2018
Abhijit Mahalunkar, John D. Kelleher, Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures, 2018, p189--198
Hunter, E. and Mac Namee, B. and Kelleher, J., Using a socioeconomic segregation burn-in model to initialise an agent-based model for infectious diseases, JASSS, 21, (4), 2018
Rogers, E., Ross, R.J., Kelleher, J.D., Evaluating sequence discovery systems in an abstraction-aware manner, IFIP Advances in Information and Communication Technology, 519, 2018, p261-272
Annika Lindh, Robert J. Ross, Abhijit Mahalunkar, Giancarlo Salton, John D. Kelleher, Generating Diverse and Meaningful Captions, 2018, p176--187
Bacher, I. and Mac Namee, B. and Kelleher, J.D., The Code Mini-Map Visualisation: Encoding Conceptual Structures Within Source Code, (8530140), 2018, pp127-131
Mahalunkar, A. and Kelleher, J.D., Using regular languages to explore the representational capacity of recurrent neural architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11141 LNCS, 2018, p189-198
, Modular mechanistic networks: On bridging mechanistic and phenomenological models with deep neural networks in natural language processing, CLASP Papers in Computational Linguistics: Proceedings of the Conference on Logic and Machine Learning in Natural Language (LaML 2017), 2017
Hines, A. and Kelleher, J.D., A framework for post-stroke quality of life prediction using structured prediction, (7965672), 2017
, The Code-Map Metaphor - A Review Of Its Use Within Software Visualisations, International Conference on Information Visualization Theory and Applications, 2017
SchÃŒtte, N. and Mac Namee, B. and Kelleher, J., Robot perception errors and human resolution strategies in situated humanâ"robot dialogue, Advanced Robotics, 31, (5), 2017, p243-257
, Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis, arXiv preprint arXiv:1703.10571, 2017
, What is not where: the challenge of integrating spatial representations into deep learning architectures, CLASP Papers in Computational Linguistics: Proceedings of the Conference on Logic and Machine Learning in Natural Language (LaML 2017), 2017
, Back to the Future: Logic and Machine Learning, 2017
, An Analysis of the Application of Simplified Silhouette to the Evaluation of k-means Clustering Validity, International Conference on Machine Learning and Data Mining in Pattern Recognition, 2017
Rogers, E., Ross, R.J., Kelleher, J.D., Tackling the interleaving problem in activity discovery, Advances in Intelligent Systems and Computing, 619, 2017, p313-314
, Incremental Joint Modelling for Dialogue State Tracking, Proc. SEMDIAL 2017 (SaarDial) Workshop on the Semantics and Pragmatics of Dialogue, 2017
Namee, B.M. and Kelleher, J.D. and Fitzpatrick, N., Assessing the usefulness of different feature sets for predicting the comprehension difficulty of text, 2086, 2017, pp12-25
Hunter, E. and Namee, B.M. and Kelleher, J., A taxonomy for agent-based models in human infectious disease epidemiology, JASSS, 20, (3), 2017
Bacher, I. and Namee, B.M. and Kelleher, J.D., The code-map metaphor: A review of its use within software visualisations, 3, 2017, pp17-28
Salton, G.D. and Ross, R.J. and Kelleher, J.D., Idiom type identification with smoothed lexical features and a maximum margin classifier, 2017-September, 2017, pp642-651
, Towards a Computational Model of Frame of Reference Alignment in Swedish Dialogue, In Proceedings of the Sixth Swedish Language Technology Conference (SLTC), 2016
, Fundamentals of Machine Learning for Neural Machine Translation, European Translation Forum, 2016
Rogers, E., Kelleher, J.D., Ross, R.J., Using topic modelling algorithms for hierarchical activity discovery, Advances in Intelligent Systems and Computing, 476, 2016, p41-48
Hunter, E. and Namee, B.M. and Kelleher, J., An open data driven epidemiological agent-based model for Irish towns, 1751, 2016, pp92-103
, A Corpus of Annotated Irish Traditional Dance Music Recordings: Design and Benchmark Evaluations, Proceedings of the 17th International Society for Music Information Retrieval Conference, ISMIR 2016, New York City, United States, August 7-11, 2016, 2016
, The Role of Perception in Situated Spatial Reference, Specialist Meeting on Universals and Variation in Spatial Referencing across Cultures and Languages (Spatial 2016), 2016
, Idiom Token Classification with Distributed Semantics, Proceedings of the 24th Irish Conference on Artificial Intelligence and Cognitive Science, 2016
Bacher, I. and Namee, B.M. and Kelleher, J.D., On using tree visualisation techniques to support source code comprehension, (7780163), 2016, pp91-95
Rogers, E. and Kelleher, J.D. and Ross, R.J., Towards a deep learning-based activity discovery system, 1751, 2016, pp184-191
Salton, G.D. and Ross, R.J. and Kelleher, J.D., Idiom token classification using sentential distributed semantics, 1, 2016, pp194-204
Kerr, A. and Kelleher, J.D., The Recruitment of Passion and Community in the Service of Capital: Community Managers in the Digital Games Industry, Critical Studies in Media Communication, 32, (3), 2015, p177-192
, Changing perspective: Local alignment of reference frames in dialogue, Proceedings of SEMDIAL (goDIAL), 2015
, Fundamentals of Machine Learning for Predictive Analytics: Algorithms, Worked Examples, and Case Studies, 2015
, Reformulation Strategies of Repeated References in the Context of Robot Perception Errors in Situated Dialogue, Proceedings of the Workshop on Spatial Reasoning and Interaction for Real-World Robotics at the International Conference on Intelligent Robots and Systems (IROS), 2015
, A Model for Attention-Driven Judgements in Type Theory with Records, Interactive Meaning Construction A Workshop at IWCS 2015, 2015
, Priming and alignment of frame of reference in situated conversation, Proceedings of SemDial 2014 (DialWatt): The 18th Workshop on the Semantics and Pragmatics of Dialogue, Edinburgh, September 1-3, 2014, 2014
, The effect of sensor errors in situated human-computer dialogue, Proceedings of the Third Workshop on Vision and Language: A Workshop of the 25th International Conference on Computational Linguistics (Coling), 2014
, TCDSCSS: Dimensionality Reduction to Evaluate Texts of Varying Lengths-an IR Approach, SemEval 2014, 2014
, DIT: Summarisation and Semantic Expansion in Evaluating Semantic Similarity, SemEval 2014, 2014
, Exploration of functional semantics of prepositions from corpora of descriptions of visual scenes, Proceedings of the Third Workshop on Vision and Language, 2014
Li, Y. and Mac Namee, B. and Kelleher, J., Expecting the unexpected: Measure the uncertainties for mobile robot path planning in dynamic environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8069 LNAI, 2014, p363-374
, Perception Based Misunderstandings in Human-Computer Dialogues, Proceedings of SemDial 2014 (DialWatt): The 18th Workshop on the Semantics and Pragmatics of Dialogue, Edinburgh, September 1-3, 2014, 2014
Li, Y., Mac Namee, B., Kelleher, J., Expecting the unexpected: Measure the uncertainties for mobile robot path planning in dynamic environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8069 LNAI, 2014, p363-374
SchÃŒtte, N. and Kelleher, J. and Namee, B.M., Clarification dialogues for perception-based errors in situated human-computer dialogues, 2014, pp25-26
Ross, R.J. and Kelleher, J., Accuracy and timeliness in ML based activity recognition, WS-13-13, 2013, pp39-46
Ross, R., Kelleher, J., A comparative study of the effect of sensor noise on activity recognition models, Communications in Computer and Information Science, 413 CCIS, 2013, p151-162
, Towards an automatic identification of functional and geometric spatial prepositions, Proc. of PRE-CogSci, 2013
Dunne, M., Mac Namee, B., Kelleher, J., The turning, stretching and boxing technique: A step in the right direction, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7502 LNAI, 2012, p363-369
, CONTENT RETRIEVAL SYSTEM, 2012
Strunkin, D. and Namee, B.M. and Kelleher, J.D., An investigation into feature selection for oncological survival prediction, (6209083), 2012, pp764-768
, Stereoscopic Avatar Interfaces: A study to Determine what Effect, if any, 3d Technology has at Increasing the Interpretability of an Avatar's Gaze into the Real-World, Proceedings of the International Workshop on Multimodel Analyses for Human Machine Interaction at IVA, 2012
Cahill, V., Boukerche, A., Theodoropoulous, G., El Saddik, A. , Message from the chairs, 2012, - ix-x
Hawes, N. and Klenk, M. and Lockwood, K. and Horn, G.S. and Kelleher, J.D., Towards a cognitive system that can recognize spatial regions based on context, 1, 2012, pp200-206
Hois, J. and Ross, R.J. and Kelleher, J.D. and Bateman, J.A., CoSLI 2011 Computational Models of Spatial Language Interpretation and Generation - Preface, 759, 2011, ppIII-IV
, Visual salience and the other one, Salience: Multidisciplinary Perspectives on Its Function in Discourse, 2011
, Automatic Annotation of Referring Expression in Situated Dialogues, International Journal Of Computational Linguistics And Applications, 2011
Sloan, C. and Kelleher, J.D. and Namee, B.M., Feasibility study of utility-directed behaviour for computer game agents, (5), 2011
, Proceedings of the Cognitive Science 2011 Workshop on Computational Models of Spatial Language Interpretation and Generation (CoSLI-2), 2011
Sloan, C. and Kelleher, J.D. and Mac Namee, B., Feeling the ambiance: Using smart ambiance to increase contextual awareness in game agents, 2011, pp298-300
Kelleher, J.D. and Ross, R.J. and Sloan, C. and Namee, B.M., The effect of occlusion on the semantics of projective spatial terms: A case study in grounding language in perception, Cognitive Processing, 12, (1), 2011, p95-108
Kelleher, J. and Ross, R. and Mac Namee, B. and Sloan, C., Situating spatial templates for human-robot interaction, FS-10-05, 2010, pp145-146
SchÃŒtte, N. and Kelleher, J. and Mac Namee, B., Visual salience and reference resolution in situated dialogues: A corpus-based evaluation, FS-10-05, 2010, pp109-114
Hanlon, N., Mac Namee, B., Kelleher, J., Just say it: An evaluation of speech interfaces for augmented reality design applications, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6206 LNAI, 2010, p134-143
, Navigating the corridors of power: using RFID and compass sensors for robot localisation and navigation, Proceedings of the 11th Conference Towards Autonomous Robotic Systems, 2010
Ross, R. and Hois, J. and Kelleher, J., Cosli 2010 computational models of spatial language interpretation: Preface, 620, 2010, ppIII-IV
, Topology in compositie spatial terms, Proceedigns of the International Conference on Spatial Cognition 2010: Poster Presentations, 2010
, Proceedings of the Spatial Cognition 2010 Workshop on Computational Models of Spatial Language Interpretation and Generation (CoSLI), 2010
, TSB Technique: Increasing a User's Sense of Immersion with Intelligent Virtual Agents, Proceedings of the 21st. Irish National Conference on Artificial Intelligence and Cognitive Science Student Symposium, 2010
, Models of Spatial Language Interpretation at Spatial Cognition 2010 (COSLI-2010)., Proceedings of the Workshop on Computational, 2010
, Scalable Multi-modal Avatar Interface for Multi-user Environments, Proceedings of the International Conference on Computer Animation and Social Agents CASA, 2010
, Helmsman, Set a Course: Using a Compass and RFID Tags for Indoor Localisation and Navigation, Proceedings of the 21st Irish Conference on Artificial Intelligence and Cognitive Science, 2010
Kelleher, J. and Sloan, C. and Mac Namee, B., An investigation into the semantics of English topological prepositions, Cognitive Processing, 10, (SUPPL. 2), 2009, pS233-S236
, A Mobile Multimodal Dialogue System for Location Based Services, Proceedings of the 9th. Annual Information Technology & Telecommunications Conference (IT&T), 2009
Kelleher, J.D. and Costello, F.J., Applying computational models of spatial prepositions to visually situated dialog, Computational Linguistics, 35, (2), 2009, p271-306
, Intelligent virtual agent: creating a multi-modal 3D avatar interface, Proceedings of the 9th. Annual Information Technology & Telecommunications Conference (IT&T), 2009
, Stepping Off the Stage, Proceedings of the 22nd Annual Conference on Computer Animation and Social Agents (CASA '09), 2009
, A Review of Negation in Clinical Texts, 2008
, Medical language processing for patient diagnosis using text classification and negation labelling, Proceedings of the Second i2b2 Shared-Task Workshop on Challenges in Natural Language Processing for Clinical Data, American Medical Informatics Association Annual conference (AMIA '08), 2008
Kelleher, J.D. and Mac Namee, B., Referring expression generation challenge 2008 DIT system descriptions, 2008, pp221-224
Brenner, M. and Kelleher, J. and Hawes, N. and Wyatt, J., Mediating between qualitative and quantitative representations for task-orientated human-robot interaction, 2007, pp2072-2077
, Proceedings of the 4th ACL-SIGSEM Workshop on Prepositions at ACL-2007., 2007
, DIT frequency based incremental attribute selection for GRE., In Proceedings of the MT Summit XI Workshop Using Corpora for Natural Language Generation: Language Generation and Machine Translation (UCNLG+MT), 2007
, A computational model of the referential semantics of projective prepositions, Syntax and Semantics of Prepositions, 2006
Kruijff, G.-J.M. and Kelleher, J.D. and Berginc, G. and Leonardis, A., Structural descriptions in human-assisted robot visual learning, 2006, 2006, pp343-344
, DIT Speech Corpus, 2006
, Spatial prepositions in context: The semantics of near in the presence of distractor objects, Proceedings of the Third ACL-SIGSEM Workshop on Prepositions, 2006
Kelleher, J.D., Attention driven reference resolution in multimodal contexts, Artificial Intelligence Review, 25, (1-2), 2006, p21-35
Kruijff, G.-J.M., Kelleher, J.D., Hawes, N., Information fusion for visual reference resolution in dynamic situated dialogue, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4021 LNAI, 2006, p117-128
Kelleher, J.D. and Kruijff, G.-J.M., Incremental generation of spatial referring expressions in situated dialog, 1, 2006, pp1041-1048
, Handling Spatial Reference in Visually-Situated Dialogs (invited presentation), brandial'06, 2006
Kelleher, J.D. and Kruijff, G.-J.M. and Costello, F.J., Proximity in context: An empirically grounded computational model of proximity for processing topological spatial expressions, 1, 2006, pp745-752
Kelleher, J. and Costello, F. and Van Genabith, J., Dynamically structuring, updating and interrelating representations of visual and linguistic discourse context, Artificial Intelligence, 167, (1-2), 2005, p62-102
, Cognitive representations of projective prepositions, Proceedings of the Second ACL-Sigsem Workshop of The Linguistic Dimensions of Prepositions and their Use in Computational Linguistic Formalisms and Applications, 2005
, A context-dependent model of proximity in physically situated environments, Proceedings of the 2nd ACL-SIGSEM Workshop on The Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications, Colchester, UK, 2005
, Integrating visual and linguistic salience for reference resolution, AICS'05, 2005
, Protocols from perceptual observations 103--136 Reiter, E., S. Sripada, J. Hunter, J. Yu and I. Davy Choosing words in computer-generated weather forecasts 137--169 Reiter, E., see Roy, D. 1--12 Roy, D., Artificial Intelligence, 2005
, A context-dependent algorithm for generating locative expressions in physically situated environments, Proceedings of ENLG-05, Aberdeen, Scotland, 2005
Kelleher, J. and Van Genabith, J., Exploiting visual salience for the generation of referring expressions, 2, 2004, pp911-916
, Analogy hy Alignment: On Structure Mapping and Similarity, Stairs 2004: Proceedings of the Second Starting Ai Researchers' Symposium, 2004
, Context-sensitive word selection for single-tap text entry, Stairs 2004: Proceedings of the Second Starting Ai Researchers' Symposium, 2004
Kelleher, J. and Van Genabith, J., Visual salience and reference resolution in simulated 3-D environments, Artificial Intelligence Review, 21, (3), 2004, p253-267
, Think and Spell: Context-Sensitive Predictive Text for an Ambiguous Keyboard Brain-Computer Interface Speller, Biomedizinische Technik, 2004
, A perceptually based computational framework for the interpretation of spatial language, 2003
, Dynamically Updating and Interrelating Representations of Visual and Linguistic Discourse (Draft), 2003
, A false colouring real time visual saliency algorithm for reference resolution in simulated 3-d environments, Proceedings of the Conference on Artifical Intelligence and Cognitive Science (AICS'03), 2003
, SONAS: Multimodal, Multi-User Interaction with a Modelled Environment, Spatial Cognition: Foundations and applications, 2000
, Scalable Multi-modal Avatar Interface for Multi-user Environments
, Using Anchor Points to Define and Transfer Spatial Regions Based on Context
, Using the Situational Context to Resolve Frame of Reference Ambiguity in Route Descriptions
, Investigating the role of priming and alignment of perspective in dialogue
, A Review of Negation in Clinical Texts: DIT Technical Report: SOC-AIG-001-08
, Putting Things ``Between'' Perspective
Research Expertise
Description
My research interests and expertise lie at the intersection of Artificial Intelligence (AI), machine learning, natural language processing, and the field of AI for Medicine. I have authored several books in the fields of machine learning and data science, including: "Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies" (MIT Press, 2020), co-authored with Brian Mac Namee and Aoife D'arcy; "Deep Learning" (MIT Press, 2019), offering a deep dive into this transformative branch of AI; and "Data Science" (MIT Press, 2018), co-authored with Brendan Tierney, offering an encompassing overview of this dynamic field. In the domain of natural language processing (NLP), my recent focus has been on unraveling the intricacies of large language models, particularly in understanding the types of linguistic information encoded within them. This research often involves probing the vector representations generated by these models. Other topics that I have worked on in this field of natural language processing include machine translation, and the related problem of natural language to source code generation. Examples of recent publications on these topics include: "Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio" (ICASSP, 2024, doi: 10.1109/ICASSP48485.2024.10446494); "Topic Aware Probing: From Sentence Length Prediction to Idiom Identification" (arXiv preprint, 2024, doi: 10.48550/arXiv.2403.02009); "Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality" (International Conference on Artificial Neural Networks, 2023, doi: 10.1007/978-3-031-44204-9_41); "Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space" (Proceedings of the 19th Workshop on Multiword Expressions, 2023, doi: 10.18653/v1/2023.mwe-1.8); and "Adaptive Machine Translation with Large Language Models" (Proceedings of the 24th Annual Conference of the European Association for Machine Translation, 2023, url: https://aclanthology.org/2023.eamt-1.22). My work on AI for Medicine primarily revolves around stroke research. Spanning various aspects including prevention, acute treatment, and rehabilitation, my recent publications in this domain include: "Predictors of social risk for post-ischemic stroke reintegration" (Scientific Reports, 2024, doi: 10.1038/s41598-024-60507-7); "Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content Analysis" (IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023); "A review of risk concepts and models for predicting the risk of primary stroke" (Frontiers in Neuroinformatics, 2022, doi: 10.3389/fninf.2022.883762); "Age-specific models to capture the change in risk factor contribution by age to short-term primary ischemic stroke risk" (Frontiers in Neurology, 2022, doi: 10.3389/fneur.2022.803749)Recognition
Awards and Honours
Professor of TU Dublin